Complex illustrations of large structures or intricate arrangements, such as electrical wiring diagrams, are commonly depicted in paper/hard copy form consisting of multiple pages of drawings. Alternatively, the separate drawings may be depicted in electronic form. The drawings contain large amounts of information regarding each element of the drawing and the corrections and relationships among the elements and among the set of drawings. Some of the information contained in the drawings is explicit, such as labels or other text. Other sources of drawing information are implicit, such as the symbols or configurations.
When a user needs information concerning a relatively small part of the structure or arrangement depicted in the set of drawings, the user must manually search through each page of the large sets of drawings, either on paper or on-line. For example, in industries that depend on complex technical drawings, manuals and parts catalogs for information about its systems, users must manually search many drawings before they can perform maintenance or troubleshoot the system. This typically becomes a lengthy process because the user must study the drawings to determine the way in which the drawings relate to each other and ensure he has all the drawings concerning the particular part of the system at issue. For instance, a wire or circuit from one drawing may be continued on one or more of the other drawings in the set. Similarly, the same circuit breaker may appear on several drawings, implying that wires connected to the circuit breaker on each drawing form a continuous circuit across the drawings. In addition to searching the drawing sets, the user also may have to refer to large parts catalogs or other manuals for more information about a certain element represented in the drawings. Searching the hard copies of the parts catalogs and/or manuals is tedious and time-consuming because of the massive amounts of information they contain. Even if the drawing sets, parts catalogs and/or manuals are on-line, the user nevertheless must repeatedly “pan” and “zoom” to find the exact information that they need.
Once users collect all of the drawings necessary to provide a comprehensive view of the system upon which they plan to work, they must carry the drawings, catalogs and/or manuals with them to perform the work. Otherwise, the user runs the risk of having to repeatedly return to the central repository of the drawings, catalogs and manuals. If the user realizes he needs drawings of another part of the system while working, then he must again commence the lengthy searches described above.
As the above discussion illustrates, the process of manually locating and attaining specific drawings from a large set of drawings for a complex structure or intricate arrangement, such as an electrical wiring diagram, is a daunting task, even for an experienced user. The process gets much more complicated when the user must also obtain all the drawings connected or related to a respective portion of the drawings at issue and/or all the information regarding particular elements within the drawings that is provided by part catalogs or other manuals. For example, finding each occurrence of a particular part number, detail label or text that appears on more than one sheet generally becomes a very lengthy process. Thus, manually searching large sets of drawings for particular parts of a system and obtaining all the drawings and/or information related to that part, is an inefficient, error-prone and expensive endeavor.
The conventional approach to providing users with faster and more accurate access to information contained in large sets of graphic files is based upon manually inserting links and supporting information into an electronic graphic file. In this regard, the conventional approach to electronic graphic text searching begins with converting all legacy electronic or hard copy drawings to an electronic format that will enable functionality to be embedded into the graphics, such as a computer graphics metafile (CGM) format. Once the graphics are properly formatted, the system builder manually re-authors the data in the drawings. To manually re-author the data, the system builder must examine each electronic drawing and manually create hundreds of individual mouse sensitive areas (“hotspots”) for each drawing. The multitude of hotspots contain the single lines of text and the blocks of texts within the graphic file. The system builder also must create programs to instruct the system on how to search the text within the graphic files and what to do when the user points at or clicks on each hotspot with his mouse. This approach eventually creates a system for providing users with fast access to text search capabilities for large sets of graphic files, such that the user may find each occurrence of particular text, whether the text is in a single line or spans multiple lines in a text block. Unfortunately, this approach is also inefficient, error-prone and prohibitively expensive because of the significant amount of manual labor required to re-author the graphic files. Thus, electronic information system builders often resist re-authoring graphic files even though the resulting graphic files would provide users with fast and accurate access to information contained in large sets of drawings, parts catalogs and/or manuals.
For the reasons discussed above, there exists a need for a system that processes complex graphic files to provide users with fast and accurate access to information contained in large sets of drawings, parts catalogs and/or manuals. More particularly, the need is for a system that efficiently recognizes text so as to support enhanced text searching functionality.